We included a total of 41 patients with monogenic lupus and 82 patients with classic lupus. Within the classic SLE group, the average age was 11.65 ± 1.87 years, with nine male patients (male:female ratio of 1:8.1), and six (7.3%) patients had a family history. In the monogenic lupus group, the average age was 3.47 ± 4.18 years, with 20 male patients (male:female ratio of 1:1.05), and nine (22%) patients had a family history. Both groups showed statistically significant differences in terms of age, gender, and family history (P < 0.05) (Table 1).

A total of 18 different gene mutations were identified among the 41 pediatric patients, as shown in Table 2. Out of these, 26 cases were associated with type I IFN pathway disorders, including six cases with adenosine deaminase 2 (ADA2) gene mutations, five cases with helicase C domain 1 gene mutations, four cases with three prime repair exonuclease 1 gene mutations, three cases with stimulator of interferon gene 1 mutations, two cases with ribonuclease H2 subunit C gene mutations, two cases with tartrate-resistant acid phosphatase gene mutations, two cases with proteasome subunit beta type-8 gene mutations, one case with RNA-editing enzyme adenosine deaminase RNA specific 1 gene mutation, and one case with sterile alpha motif and HD domain-containing protein 1 gene mutation. Additionally, five cases were linked to RAS-associated autoimmune leukoproliferative disorder, comprising two cases with Kirsten rat sarcoma viral oncogene homolog (KRAS) gene mutations and three cases with neuroblastoma RAS viral oncogene homolog gene mutations. Furthermore, four cases were related to immune tolerance pathways, with three cases having phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit delta gene mutations, and one case with an Ikaros family zinc finger proteins 1 gene mutation. There was also one case with C1s deficiency. Other mutated genes included two cases with tumor necrosis factor alpha-induced protein 3 gene mutations, one case with solute carrier family 7 member 7 gene mutation, one case with peptidase D gene mutation, and one case with Shwachman–Bodian–Diamond syndrome (SBDS) gene mutation. Some of these gene loci have been previously reported by our team [13,14,15,16], while others have been documented in various literature [17,18,19,20,21,22,23,24,25,26,27,28,29]. Nine loci from seven genes have not been reported (Table 2). Although two loci of KRAS have been reported, they were not related to lupus. In addition, our center reported for the first time that the SBDS gene was related to SLE [29].

The primary clinical manifestations of both groups are compared in Table 3. Although skin and mucosal involvement were common in both groups, classic SLE was more likely to present with acute/subacute rashes (67.1%), primarily typical malar rashes (58.5%). In contrast, patients in the monogenic lupus group were more likely to exhibit chronic rashes (39%), particularly chilblain-like rashes (19.5%), nodular erythema (12.2%), and livedo reticularis (19.5%). Hematologic system involvement was more common in classic SLE, mainly manifested as hemolytic anemia (53.7%), whereas monogenic lupus primarily exhibited abnormal liver function (65.9%) in the gastrointestinal system. Neuropsychiatric involvement, on the other hand, was more common in monogenic lupus (46.3%), with abnormal muscle tone being the most common (22%), followed by seizure episodes (14.6%). Monogenic lupus also exhibited more significant respiratory system involvement (53.7%), primarily with pulmonary interstitial involvement (27.8%). Renal involvement was more frequent in the classic lupus group (56.1%). In terms of other clinical presentations, patients with monogenic lupus were more likely to have a history of recurrent infections (31.7%), accompanied by fever (63.4%), lymphadenopathy/hepatosplenomegaly (56.1%), and growth and developmental delay (48.8%). Regarding complications, the classic SLE group was more prone to cytomegalovirus (CMV) infection (70.7%). There were no statistically significant differences in other affected systems.

While the monogenic lupus group can also exhibit various positive autoantibodies, the classic SLE group is more likely to present with lupus-specific antibodies, such as antinuclear antibodies, anti-double strand-DNA antibodies, anti-Smith antibodies, anti-ribonuclear protein (RNP) antibodies, anti-Sjogren's syndrome antigen A antibodies, anti-ribosomal RNP antibodies, anti-Ro-52 antibodies, anti-complement antibodies, anti-nucleosome antibodies, and lupus anticoagulants. Individuals in the classic SLE group are also more likely to have decreased complement levels, all of which demonstrate significant statistical differences, as shown in Table 4.

Head imaging findings of the two groups of patients, including head computed tomography, head magnetic resonance imaging/magnetic resonance angiography/magnetic resonance venography, are compared in Table 4. The monogenic lupus group showed a higher proportion of patients with intracranial calcifications and brain atrophy, with significant statistical differences.

The variables that showed differences between the two groups in the univariate analysis were included in the LASSO regression analysis. After LASSO regression selection (Fig. 2a), the subsequent seven variables emerged as significant predictive factors for monogenic lupus: age of onset, history of recurrent infections, intracranial calcifications, growth and developmental delay, abnormal muscle tone, lymphadenopathy/hepatosplenomegaly, and chilblain-like skin rash. Notably, the variables in the model are independent. The regression coefficients for these variables were − 1.5864, 0.9920, 0.6654, 0.3318, 0.2103, 0.1179, and 0.0896, respectively (Fig. 2b). When the coefficients are scaled back to the original units of the variables, the resulting linear prediction model for monogenic lupus is as follows: 0.2906977 − 1.4124018 × age of onset + 15.2761768 × recurrent infections + 7.5899250 × intracranial calcifications + 3.5908622 × growth and developmental delay + 3.0491924 × abnormal muscle tone + 1.1751209 × lymphadenopathy/hepatosplenomegaly + 1.2324701 × chilblain-like skin rash.

LASSO regression coefficient profiles and model variables with their coefficients. a LASSO coefficient profiles of the radiomic featuresl; b model variables and their coefficients. LASSO least absolute shrinkage and selection operator, AUC area under the receiver operating characteristic curve

The LASSO model achieved an area under the receiver operating characteristic (ROC) curve (AUC) of 0.97 [95% confidence interval (CI) = 0.92–0.97] in the test set (Fig. 3a). We also constructed a logistic regression model and evaluated its performance, resulting in an AUC of 0.87 (95% CI = 0.75–0.87). Comparison between the two models demonstrated the superiority of the LASSO model (Fig. 3a). Furthermore, the LASSO model exhibited an accuracy of 0.86, a precision of 0.81, a recall of 1, and an F1 score of 0.89, indicating excellent predictive performance of this model. We assessed the risk score prediction for monogenic lupus using the ROC curve, which yielded an AUC of 0.98 (95% CI = 0.97–1.00) (Fig. 3b). Utilizing the Youden index, we identified a cutoff score of − 9.032299, suggesting that patients with SLE/lupus-like who have a predictive model score greater than − 9.032299 are at a higher risk of having monogenic lupus, with a risk probability of 0.766 (sensitivity = 92.7%, specificity = 98.8%). We have represented the risk factors in a nomogram (Fig. 4) to facilitate clinicians in intuitively assessing a patient’s risk of developing monogenic lupus.

Comparison and risk prediction of monogenic lupus using ROC analysis. a The comparison of ROC curves between LASSO regression and logistic regression; b ROC curve for risk score prediction of monogenic lupus. LASSO least absolute shrinkage and selection operator, ROC receiver operating characteristic, AUC area under the ROC curve

Nomogram for probability of monogenic lupus